Moritz, C., J. L. Patton, C. J. Conroy, J. L. Parra, G. C. White, and

Impact of a Century of Climate Change on
Small-Mammal Communities in Yosemite National
Park, USA
Craig Moritz, et al.
Science 322, 261 (2008);
DOI: 10.1126/science.1163428
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References and Notes
1. C. Parmesan, Annu. Rev. Ecol. Evol. Syst. 37, 637
(2006).
2. R. Wilson, D. Gutierrez, J. Gutierrez, V. Monserrat, Glob.
Change Biol. 13, 1873 (2007).
3. J. Lenoir, J. Gegout, P. Marquet, P. de Ruffray, H. Brisse,
Science 320, 1768 (2008).
4. M. B. Bush, Glob. Ecol. Biogeogr. 11, 463 (2002).
5. Materials and methods are available as supporting
material on Science Online.
6. M. B. Bush, H. Hooghiemstra, in Climate Change and
Biodiversity, T. E. Lovejoy, L. Hannah, Eds. (Yale Univ.
Press, New Haven, CT, 2005), pp. 125–137.
7. J. A. Pounds, M. P. L. Fogden, K. L. Masters, in Climate
Change and Biodiversity, T. E. Lovejoy, L. Hanna, Eds.
(Yale Univ. Press, New Haven, CT, 2005), pp. 70–74.
8. C. L. Cardelús, R. K. Colwell, J. E. Watkins, J. Ecol. 94,
144 (2006).
9. G. Brehm, R. K. Colwell, J. Kluge, Glob. Ecol. Biogeogr.
16, 205 (2007).
10. A. R. Wallace, Tropical Nature and Other Essays
(Macmillan, London, 1878).
11. T. Dobzhansky, Am. Sci. 38, 209 (1950).
12. L. Hannah, R. A. Betts, H. H. Shugart, in Tropical
Rainforest Responses to Climatic Change, M. B. Bush,
J. R. Flenley, Eds. (Springer Praxis, 2007), pp. 351–366.
13. J. R. Flenley, Clim. Change 39, 177 (1998).
14. M. B. Bush, M. R. Silman, D. H. Urrego, Science 303, 827
(2004).
15. F. E. Mayle, D. J. Beerling, W. D. Gosling, M. B. Bush,
Philos. Trans. R. Soc. London B Biol. Sci. 359, 499
(2004).
16. M. Bush, M. Silman, J. Quat. Sci. 19, 677 (2004).
17. D. D. Ackerly et al., Bioscience 50, 979 (2000).
18. J. Hansen et al., Proc. Natl. Acad. Sci. U.S.A. 103, 14288
(2006).
19. C. A. Deutsch et al., Proc. Natl. Acad. Sci. U.S.A. 105,
6668 (2008).
20. D. A. Clark, S. C. Piper, C. D. Keeling, D. B. Clark, Proc.
Natl. Acad. Sci. U.S.A. 100, 5852 (2003).
21. K. J. Feeley, S. Joseph Wright, M. N. Nur Supardi,
A. R. Kassim, S. J. Davies, Ecol. Lett. 10, 461 (2007).
22. O. L. Phillips, S. L. Lewis, T. R. Baker, Y. Malhi, in Tropical
Rainforest Responses to Climatic Change, M. B. Bush,
J. R. Flenley, Eds. (Springer Praxis, 2007), pp. 317–332.
23. L. Miles, A. Grainger, O. Phillips, Glob. Ecol. Biogeogr.
13, 553 (2004).
24. S. A. Cowling et al., Philos. Trans. R. Soc. London B Biol.
Sci. 359, 539 (2004).
25. J. W. Williams, S. T. Jackson, J. E. Kutzbach, Proc. Natl.
Acad. Sci. U.S.A. 104, 5738 (2007).
26. M. B. Bush, M. R. Silman, C. McMichael, S. Saatchi, Philos.
Trans. R. Soc. London B Biol. Sci. 363, 1795 (2008).
27. R. L. Peters, J. D. S. Darling, Bioscience 35, 707 (1985).
28. G.-R. Walther et al., Nature 416, 389 (2002).
Impact of a Century of Climate Change
on Small-Mammal Communities in
Yosemite National Park, USA
Craig Moritz,1,2* James L. Patton,1,2 Chris J. Conroy,1 Juan L. Parra,1,2
Gary C. White,3 Steven R. Beissinger1,4
We provide a century-scale view of small-mammal responses to global warming, without
confounding effects of land-use change, by repeating Grinnell’s early–20th century survey across
a 3000-meter-elevation gradient that spans Yosemite National Park, California, USA. Using
occupancy modeling to control for variation in detectability, we show substantial (~500 meters on
average) upward changes in elevational limits for half of 28 species monitored, consistent with the
observed ~3°C increase in minimum temperatures. Formerly low-elevation species expanded their
ranges and high-elevation species contracted theirs, leading to changed community composition at
mid- and high elevations. Elevational replacement among congeners changed because species’
responses were idiosyncratic. Though some high-elevation species are threatened, protection
of elevation gradients allows other species to respond via migration.
lthough human-driven global warming
(1) has changed phenology of species
and contributed to range expansions
(2–6), contractions of species’ ranges are less well
A
1
Museum of Vertebrate Zoology, University of California,
Berkeley, CA 94720, USA. 2Department of Integrative
Biology, University of California, Berkeley, CA 94720, USA.
3
Department of Fish, Wildlife, and Conservation Biology,
Colorado State University, Fort Collins, CO 80523, USA.
4
Department of Environmental Science, Policy and Management, University of California, Berkeley, CA 94720,
USA.
*To whom correspondence should be addressed. E-mail:
[email protected]
documented (7–10). Models of future climatechange scenarios predict large range shifts, high
global extinction rates, and reorganized communities (11, 12), but model outcomes are also highly uncertain (13, 14). Most studies of species’
responses span only a few decades—typically
from the 1960 or 1970s, which was a relatively
cool period, to the present. Such results can be
confounded by decadal-scale climate oscillations
(15) and landscape modification (8, 16). Furthermore, range shifts are uncertain when confounded
by false absences due to limited historic sampling
and inability to control for changes in detectability
between sampling periods (17, 18).
www.sciencemag.org
SCIENCE
VOL 322
29. C. Ghalambor, R. Huey, P. Martin, J. Tewksbury, G. Wang,
Integr. Comp. Biol. 46, 5 (2006).
30. R. G. Pearson, T. P. Dawson, Glob. Ecol. Biogeogr. 12,
361 (2003).
31. S. Williams, E. E. Bolitho, S. Fox, Proc. R. Soc. London B.
Biol. Sci. 270, 1887 (2003).
32. J. H. Christensen et al., in Climate Change 2007: Fourth
Assessment Report of the Intergovernmental Panel on
Climate Change, S. Solomon et al., Eds. (Cambridge Univ.
Press, Cambridge, 2007), pp. 847–940.
33. J. Kluge, M. Kessler, R. R. Dunn, Glob. Ecol. Biogeogr.
15, 358 (2006).
34. Supported by the Organization for Tropical Studies; the
Tropical Ecology Assessment and Monitoring (TEAM) project
of Conservation International; University of Connecticut
(R.K.C. and C.L.C.); UCLA (A.C.G.); U.S. NSF (DEB-0072702:
R.K.C., G.B., and J.T.L.; DEB-0640015: J.T.L.;
DEB-0639979: R.K.C.; Research Fellowship and
Dissertation Improvement Grant: C.L.C.); Sigma Phi,
Explorer’s Club, and Steven Vavra Plant Systematics Fund
(A.C.G.); and the Deutsche Forschungsgemeinschaft
(BR 2280/1-1: G.B.). We thank M. B. Bush, R. L. Chazdon,
D. A. Clark, R. R. Dunn, K. M. Kuhn, C. Rahbek, T. F. L. V. B.
Rangel, M. R. Silman, and our peer reviewers for comments.
Downloaded from www.sciencemag.org on October 10, 2008
pear unlikely, putting the focus on elevational
gradients, where range-shift gaps will develop
early for the great numbers of narrow-ranged
species. The lowland tropics lack a source pool of
species adapted to higher temperatures to replace
those driven upslope by warming, raising the
possibility of substantial attrition in species richness in the tropical lowlands.
Supporting Online Material
www.sciencemag.org/cgi/content/full/322/5899/258/DC1
Materials and Methods
Figs. S1 and S2
References
30 June 2008; accepted 2 September 2008
10.1126/science.1162547
We quantified the impact of nearly a century
of climate change on the small-mammal community of Yosemite National Park (YNP) in California, USA, by resampling a broad elevational
transect (60 to 3300 m above sea level) that
Joseph Grinnell and colleagues surveyed from
1914 to 1920 (19) (Fig. 1). Their work documented the diversity and distribution of terrestrial
vertebrates in California to establish a benchmark
for future comparison (20), and led to the concept
of the ecological niche, the importance of temperature as determinant of range boundaries, and
the notion that species respond uniquely to environmental changes (21). In contrast to most early–
20th century records, the “Yosemite Transect”
was densely sampled across elevations (Fig. 1)
and is amply documented by specimens (n =
4354), field notes (>3000 pages), and photographs
(~700) (22), enabling precise identification of both
species and sampling sites. From daily trapping
records, we estimated detectability of species in
historical as well as current surveys, permitting
the unbiased estimation of species’ “absences”
from elevational bands in both periods (23). The
transect spans YNP, a protected landscape since
1890, and allowed us to examine long-term responses to climate change without confounding
effects of land-use change, although at low to midelevations there has been localized vegetation
change relating to seral dynamics, climate change,
or both (24). Finally, analyses of regional weather
records pointed to substantial increase of the average minimum monthly temperature of 3.7°C
over the past 100 years, with notable increases
from 1910 to 1945 and from 1970 to the present
(15, 22) (fig. S1).
10 OCTOBER 2008
261
Future warming is predicted to cause substantial turnover of species within North American
National Parks, including Yosemite (25). Given
marked regional warming over the past century,
we predicted that species ranges should have
shifted upward (5, 10). This should manifest as
upward contraction of the lower range limit for
mid- to high-elevation species, upward shift of
the entire range or expansion of the upper limit
for low- to mid-elevation species, and altered community composition within elevational bands (9).
Elevational ranges of species and their habitats differed markedly between the gradual western and steep eastern slopes of the transect (19)
(Fig. 1). On the west slope, we trapped small
mammals at 121 sites compared to 56 in Grinnell’s
time (table S1), but overall effort and elevational
range (~50 to 3300 m) were comparable (22).
There were fewer sites on the east side in both
time periods (9 for Grinnell, 12 for resurveys)
because of limited extent (Fig. 1). Our analyses
of richness and turnover focused on species detectable by standardized trapping (37 species) or
by observation (6 species; table S2). To test for
elevational shifts, we applied occupancy modeling (22, 23) to the 23 west slope taxa with sufficient trapping records to estimate detectability
in both periods (tables S1 and S2 and Fig. 2). The
best detection model in a set of 36 (table S3) was
used to calculate the probability of a false absence (Pfa) across trapping sites, where a species
was not observed in one sampling period but was
in the other (Table 1). Range shifts were significant if Pfa ≤ 0.05. For each species we evaluated
eight hypothesized relationships of occupancy,
era, and elevation (fig. S2) using the 14 best detection models (table S3) to create model-averaged
occupancy-elevation profiles (Fig. 2 and fig. S3).
Conservatively, we excluded shifts that were statistically significant but biologically trivial (Fig.
3). In most cases where the Pfa test indicated an
elevation shift, occupancy models agreed (Table
1 and fig. S3). Exceptions occurred when occupancy models were weak (i.e., insufficient data)
or detected changes in occupancy at elevations
other than range limits, or when nonstandard data
(i.e., records from ad hoc collecting) were included in Pfa tests but not in occupancy models.
Elevation limits shifted mostly upward (Table
1 and Fig. 3A), and this occurred more frequently
for lower than upper limits (c2 = 4.26, df = 1, P =
0.039). Twelve of 28 (43%) west slope species
showed significant shifts in lower limits, of which
10 increased (mean = +475 m) and two, both
shrews, decreased (mean = −744 m). In contrast,
upper limits changed significantly in only seven
instances, with similar numbers of upward (n = 4,
mean = +501 m) and downward shifts (n = 3,
mean = −309 m).
High-elevation species typically experienced
range contractions, whereas low-elevation species
expanded their ranges upward (c2 = 8.8, df = 2,
P = 0.012), a pattern expected with increased
temperature. Lower range limits contracted in
50% of the high-elevation species but in only
262
10% of low-elevation species, whereas 50% of
low-elevation species expanded their upper range
compared to none of the high-elevation species
(Fig. 3B). High-elevation species contracting
(Table 1 and Fig. 2A) included the alpine chipmunk (Tamais alpinus), Belding’s ground squirrel (Spermophilus beldingi), water shrew (Sorex
palustris), and pika (Ochotona princeps). Range
collapse—increased lower limits and decreased
upper limits—was observed in two high-elevation
species: the bushy-tailed woodrat (Neotoma cinerea)
and the shadow chipmunk (T. senex) (Fig. 2B).
Parallel trends were observed on the east slope of
the Sierra for N. cinerea and S. beldingi (fig. S3).
Range contractions due to increases in lowerelevation limits were also observed for two
species formerly at mid- to high elevations [the
golden-mantled ground squirrel (Spermophilus
lateralis) and the long-tailed vole (Microtus
longicaudus)] (Table 1). Only one lowland
species contracted—the kangaroo rat (Dipodomys heermanni) showed a modest increase in
lower limit and a larger decrease in upper limit
since Grinnell’s time. Range expansions resulted
from either expanded upper limits [the pocket
mouse (Chaetodippus californicus), the California
vole (M. californicus), and the harvest mouse
(Reithrodontomys megalotis)] or expanded
lower limits (two shrews: Sorex monticola
and S. ornatus). Finally, the pinyon mouse
(Peromyscus truei) translocated upward (Fig.
2C); both upper and lower limits increased by
~500 m, but it now also occupies montane
conifer habitats on the west slope 800 to 1400
m higher after its east slope population expanded
upward by ~1000 m to cross the Sierra crest.
Elevational range shifts resulted in modest
changes in species richness and composition at
varying spatial scales. Species richness averaged
across five estimators (26) that account for nonobserved species (Fig. 3C, fig. S4, and table S4)
declined from the Grinnell era to the present
(repeated measures analysis of variance, F = 32.7
df = 1, P = 0.004). Richness estimators suggest a
slight decrease across the whole transect (currenthistoric mean estimates = −4.4 species, −9%), but
not within YNP (+1.3 species, 4%). Species richness was reduced within each life zone, with the
largest change in the Lower and Upper Sonoran
zones west of YNP. Community similarity between Grinnell’s period and the present was high
(mean similarity, S > 0.9) for the whole transect,
the park alone, and most life zones. Species composition was least similar for the Transition and
Hudsonian-Arctic zones, as expected given the
upward expansions of formerly Sonoran zone
taxa and the range shifts of high-elevation species
(Table 1).
Closely related species responded idiosyncratically to climate change (Table 1), but why species vary in response is not clear. For example,
some species of Peromyscus mice showed elevation range shifts (P. truei), whereas others
did not (P. boylii, P. maniculatus). The same is
Fig. 1. Map of surveyed sites in Grinnell (Historic) and Current surveys relative to the Yosemite
National Park boundary and life zones (upper panel), and to an averaged elevational profile (lower
panel).
10 OCTOBER 2008
VOL 322
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REPORTS
REPORTS
survey, we provide an unbiased comparison of
changes in species’ ranges at the centennial scale.
Because much of the transect spans a longprotected National Park, confounding effects of
land-use change are minimized. Even so, vegetation has changed within YNP over this period,
in part due to fire suppression (22). The park was
hardly pristine in the early 20th century, with
ranching of introduced herbivores in Yosemite
Valley and the high country recovering from historical overgrazing. As examples, expansion by
C. californicus and west slope P. truei are associated with fire-related conversion of conifer to
shrub habitats, whereas the downward shift of
S. monticola could reflect recovery of their
preferred wet meadow habitats. Increased prevalence of mesic small mammals following cessation of grazing has also been reported for an
Table 1. Analyses of elevation change for 28 west slope species. Given are
average detectability per site for Grinnell [P(G)] and current [P(C)] periods, original
elevation range, changes in upper (U) and lower (L) range limit that are significant
by the Pfa tests, the best supported form of the occupancy model (Elev, elevation;
NA, not analyzed), the cumulative Akaike’s Information Criterion weight for all
No.
1
2
Species
P(G)
P(C)
Original
elevation
range (m)
0.81
0.58
57–1160
models with those terms (w), and original Lifezone classification (18), where L and H
refer, respectively, to species with mostly low- to mid-elevation ranges (<2000 m)
and mid- to high-elevation ranges (>2000 m) in Grinnell’s time; P. maniculatus
covered the entire transect. Values in bold are further supported by occupancy
models. See fig. S4 for elevation plots and models of individual species.
Best
occupancy
model
Range limit
change (m)
Lower–Upper Sonoran (L)
+112 U
+589 U, +468 L
0.50
0.99
Lower–Upper Sonoran (L)
Upper Sonoran (L)
0.32
0.74
0.37
Upper Sonoran (L)
Upper Sonoran (L)
Canadian–Hudsonian (H)
0.48
0.74
0.53
0.48
0.78
0.39
0.83
0.32
0.56
NA
Lower–Upper Sonoran (L)
Transition–Hudsonian (H)
Transition–Hudsonian (H)
Canadian (H)
Transition–Hudsonian (H)
Canadian–Hudsonian (H)
Canadian–Arctic-Alpine (H)
Canadian–Arctic-Alpine (H)
Hudsonian–Arctic-Alpine (H)
Canadian–Arctic-Alpine (H)
0.72
NA
0.89
0.62
0.60
0.40
0.36
Lower Sonoran–Arctic-Alpine (H)
Lower Sonoran–Transition (L)
Lower Sonoran–Canadian (L)
Lower Sonoran–Transition (L)
Upper Sonoran–Transition (L)
Transition–Canadian (H)
Transition–Hudsonian (H)
0.87
0.93
57–1160
183–1220
5
6
0.28
0.32
0.99
0.19
0.93
0.97
193–914
549–914
2212–3287
7
8
9
10
11
12
13
14
15
16
Dipodomys heermanni
Microtus longicaudus
Zapus princeps
Tamias senex
Spermophilus lateralis
Sorex palustris
Neotoma cinerea*
Spermophilus beldingi*
Tamias alpinus
Ochotona princeps†
0.16
0.99
0.98
0.95
0.70
0.39
0.90
0.98
0.92
NA
0.98
0.98
0.90
0.71
0.89
0.23
0.71
0.98
0.95
NA
57–1025
623–3287
1291–3185
1402–2743
1646–3200
1658–3155
1798–3287
2286–3287
2307–3353
2377–3871
17
Peromyscus
maniculatus*
Thomomys bottae†
Spermophilus beecheyi
Neotoma macrotis
Peromyscus boylii
Sorex trowbridgii
Microtus montanus*
Tamiasciurus
douglasi*†
Tamias
quadrimaculatus
Tamias speciosus*
Thomomys monticola†
Marmota flaviventris†
0.99
NA
0.50
0.90
0.98
0.71
0.81
0.99
NA
0.82
0.91
0.97
0.88
0.98
57–3287
57–1676
61–2734
183–1646
183–2469
1160–2286
1217–3155
No change
No change
−250 U
+67 U
−122 L
No change
No change
Era*(Elev + Elev2)
NA
Era*(Elev + Elev2)
Elev + Elev2
Elev + Elev2
Elev + Elev2
Elev + Elev2
NA
NA
1229–3185
No change
NA
0.95
1.00
NA
NA
0.85
1.00
NA
NA
1494–2210
1768–3155
1905–3155
2469–3353
+50 U
+128 L, +65 U
No change
No change
Era*(Elev + Elev2)
Era*(Elev + Elev2)
NA
NA
25
26
27
28
* Similar trends are observed for east-side populations (see fig. S4).
Original life zone (H, L)
0.36
0.99
0.99
18
19
20
21
22
23
24
w
Range expansions
+505 U
Elev
Microtus californicus
Reithrodontomys
megalotis
Peromyscus truei*
Chaetodippus
californicus
Sorex ornatus
Sorex monticolus
3
4
analogous community in the Rocky Mountains
(27).
The preponderance of upward range shifts,
leading to contraction of high-elevation species
and expansions of low-elevation taxa, accords with
the predicted impacts of climate warming (5, 8, 9).
Although vegetation dynamics have likely contributed to changes at low to mid-elevation, habitat change at higher elevations is limited (15)
(fig. S6). The ~500-m average increase in elevation for affected species is also consistent with
estimated warming of +3°C, assuming a change
of temperature with elevation of ~6°C per km.
Several small-mammal taxa that responded to
changing temperature also showed large range
fluctuations during late Quaternary climate fluctuations (28), and some have declined regionally (29).
Downloaded from www.sciencemag.org on October 10, 2008
true for chipmunks (Tamias), ground squirrels
(Spermophilus), voles (Microtus), and shrews
(Sorex). Beyond original elevation range (high
versus low), life history and ecological traits were
weak predictors of which species exhibited upward shifts of their range limits (tables S5 and
S6). This was especially true for high-elevation
species with upward contraction of their lower
range limit. However, lowland species that are
short-lived and lay more litters per year (so-called
fast life-style species) were more likely to expand
their range upward than were their long-lived,
less fecund counterparts (table S5 and fig. S5).
The elevational replacements among congeners,
documented so carefully in the early 20th century
(19), are now quite different.
By applying occupancy modeling to a thoroughly documented historical record and the re-
Elev
Era*(Elev + Elev2)
+800 U
Era*(Elev + Elev2)
−485 L
Era *(Elev + Elev2)
−1003 L
Era + Elev + Elev2
Range contractions
+63 L, –293 U
Era*Elev
+614 L
Era + Elev + Elev2
+159 L, −64 U
Era + Elev + Elev2
+1007 L, −334 U
Elev +Elev2
+244 L
Era*(Elev + Elev2)
+512 L
Era + Elev + Elev2
+609 L, −719 U
Era*(Elev + Elev2)
+355 L
Elev
+629 L
Era + Elev
+153 L
NA
No change
NA
0.78
1.00
NA
NA
Transition–Hudsonian (H)
Transition–Canadian (H)
Canadian–Hudsonian (H)
Canadian–Hudsonian (H)
Canadian–Arctic-Alpine (H)
†These species were encountered by observation and/or specialized trapping and were not subject to occupancy analyses.
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10 OCTOBER 2008
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REPORTS
Fig. 2. Example elevation plots
from the west slope transect of upward range expansion (T. alpinus
and P. truei) (A and C), and
range collapse (N. cinerea) (B).
Shown are occupied (black) and
unoccupied (gray) sites, probability of false absence (Pfa),
and model-averaged occupancyelevation profiles (table S3 and
fig. S2). P. truei colonized high
elevations west of the Sierra crest
from the eastern slope. Red
marks for historical elevation
profile of T. alpinus refer to ad
hoc records.
Recent trends do not bode well for several
mid- to high-elevation species, including some endemic to the high Sierra (e.g., T. alpinus) (Fig. 3A).
Nevertheless, species diversity within Yosemite
has changed little, because range expansions compensated for retractions. Our results confirm that
protecting large-scale elevation gradients retains
diversity by allowing species to migrate in response to climate and vegetation change. The
long-recognized importance of protected landscapes has never been greater.
Fig. 3. (A) Summary of elevational
range changes across all species in
relation to life zones. Significant
(Pfa < 0.05) shifts are colored green
for range expansion and red for contraction (Table 1). Species were classified as “No Change” if range shifts
were biologically trivial (<10% of
previous elevation range) or of small
magnitude (<100 m). (B) Comparison of changes in elevation-range
limits for species that formerly had
low- to mid-elevation versus mid- to
high-elevation ranges (Table 1) across
the transect. (C) Mean (T SE) estimates of
species richness by era (bars: H, historic;
P, present; see also table S4 and fig. S4)
and community similarity (points) for individual life zones, Yosemite National Park,
and the entire transect.
Supporting Online Material
www.sciencemag.org/cgi/content/full/322/5899/261/DC1
Materials and Methods
Figs. S1 to S6
Tables S1 to S6
18 July 2008; accepted 9 September 2008
10.1126/science.1163428
264
10 OCTOBER 2008
VOL 322
SCIENCE
www.sciencemag.org
Downloaded from www.sciencemag.org on October 10, 2008
References and Notes
1. Intergovernmental Panel on Climate Change, Climate
Change 2007: Synthesis Report Contribution of Working
Groups I, II, and III to the Fourth Assessment Report of
the Intergovernmental Panel on Climate Change (IPCC,
Geneva, Switzerland, 2007).
2. C. Rosenzweig et al., Nature 453, 353 (2008).
3. C. Parmesan, G. Yohe, Nature 421, 37 (2003).
4. G. R. Walther et al., Nature 416, 389 (2002).
5. C. Parmesan, Annu. Rev. Ecol. Evol. Syst. 37, 637 (2006).
6. J. Lenoir, J. C. Gégout, P. A. Marquet, P. de Ruffray,
H. Brisse, Science 320, 1768 (2008).
7. R. J. Rowe, J. Biogeogr. 32, 1883 (2005).
8. R. Hickling, D. B. Roy, J. K. Hill, R. Fox, C. D. Thomas,
Glob. Change Biol. 12, 450 (2006).
9. R. J. Wilson, D. Gutierrez, J. Gutierrez, V. J. Monserrat,
Glob. Change Biol. 13, 1873 (2007).
10. C. D. Thomas, A. M. A. Franco, J. K. Hill, Evolution Int. J.
Org. Evolution 21, 415 (2006).
11. C. D. Thomas et al., Nature 427, 145 (2004).
12. J. W. Williams, S. T. Jackson, Front. Ecol. Environ 5, 475
(2007).
13. A. J. Davis, L. S. Jenkinson, J. H. Lawton, B. Shorrocks,
S. Wood, Nature 391, 783 (1998).
14. R. G. Pearson et al., J. Biogeogr. 33, 1704 (2006).
15. C. I. Millar, R. D. Westfall, D. L. Delany, J. C. King,
L. J. Graumlich, Arct. Antarct. Alp. Res. 36, 181 (2004).
16. W. Jetz, D. S. Wilcove, A. P. Dobson, PLoS Biol. 5, e157
(2007).
17. J. K. Hill et al., Proc. R. Soc. Lond. B. Biol. Sci. 269, 2163
(2002).
18. L. P. Shoo, S. E. Williams, J. M. Hero, Biol. Conserv. 125,
335 (2005).
19. J. Grinnell, T. Storer, Animal Life in the Yosemite (Univ. of
California Press, Berkeley, CA, 1924).
20. J. Grinnell, Pop. Sci. Mon. 77, 163 (1910).
21. J. Grinnell, Am. Nat. 51, 115 (1917).
22. See supporting material on Science Online.
23. D. I. MacKenzie et al., Inferring Patterns and Dynamics of
Species Occurrence (Elsevier, San Diego, 2006).
24. A. Guarin, A. H. Taylor, For. Ecol. Manage. 218, 229 (2005).
25. C. E. Burns, K. M. Johnston, O. J. Schmitz, Proc. Natl.
Acad. Sci. U.S.A. 100, 11474 (2003).
26. A. Chao, in Encyclopedia of Statistical Sciences,
N. Balakrishnan, C. B. Read, B. Vidakovic, Eds.
(Wiley, New York, 2005).
27. R. J. Rowe, Am. Nat. 170, 242 (2007).
28. D. K. Grayson, Quat. Sci. Rev. 25, 2964 (2006).
29. E. A. Beever, P. E. Brussard, J. Berger, J. Mammal. 84, 37
(2003).
30. Supported by funding from the Yosemite Foundation, the
National Parks Service, and NSF (DEB 0640859).
Assistance was received from A. Chang, H. Shofi, K. Tsao,
D. Yang, W. Monahan, R. Hijmans, and M. Koo. L. Chow
(U.S. Geological Survey Yosemite) and S. Thompson
(Yosemite National Park) stimulated and participated in
the project. Comments from R. Colwell, M. Power,
F. Hamer, and L. Shoo improved this manuscript.
www.sciencemag.org/cgi/content/full/322/5889/261/DC1
Supporting Online Material for
Impact of a Century of Climate Change on Small-Mammal Communities in
Yosemite National Park, USA
Craig Moritz,* James L. Patton, Chris J. Conroy, Juan L. Parra, Gary C. White, Steven R.
Beissinger
*To whom correspondence should be addressed. E-mail: [email protected]
Published 10 October 2008, Science 322, 261 (2008)
DOI: 10.1126/science.1163428
This PDF file includes:
Materials and Methods
Figs. S1 to S6
Tables S1 to S6
References
SUPPORTING ONLINE MATERIAL
Materials And Methods
A. Evidence for Climate Change in Yosemite Region.
Evidence from various independent sources point to an increase in average temperature at the
state level (S1) and locally in the area of Yosemite National Park and the transect (S2).
Direct evidence of warming in the area was obtained from weather station data available from
NCDC (http://www.ncdc.noaa.gov/oa/ncdc.html) and WRCC (http://www.wrcc.dri.edu/).
Average monthly minimum temperature in Yosemite Valley has experienced a general increase
during the last century whereas maximum temperature shows slight or no increase (Fig. S1).
Linear regression of monthly averages of minimum temperature for the Yosemite Headquarters
station indicate a general increase of 3.9 C in January and 5.3 C in July. A similar analysis done
by Millar et al. (S2) but combining data from two other stations (Sacramento, CA and Mina,
NV) revealed an average increase of 3.7 C when using annual averages of minimum temperature.
Millar et al. (S2) also registered changes in vegetation growth recorded in tree rings and invasion
of snowfield slopes that match tightly with changes in minimum temperature and also variability
in precipitation. LaDochy et al. (S1) performed an analysis of climate trends at the state level
using weather station data from 1950 – 2000 and found an average warming of 1.0 C during this
period. Comparison of interpolated climate surfaces for California indicate considerable spatial
variation in both the magnitude and direction of climate change (S3).
B. Sampling Design and Field Methods
We identified the field sites visited by the 1914–1920 Grinnell Survey from a
combination of their original field notes and maps that are archived at the Museum of Vertebrate
Zoology (MVZ; http://mvz.berkeley.edu/Grinnell/). Written descriptions enabled us to precisely
relocate and resample many of the same sites. Field teams spent a minimum of 10 days at each
site, and sampled each of the major habitats within a radius of approximately 1 km (chaparral,
woodland, forest, meadow, riparian, talus, etc.). Most sites were surveyed one time during the 3year period, but several were revisited two or more times. All field notes, photographs,
datasheets, and maps are archived in the Museum of Vertebrate Zoology.
During the Grinnell period, small mammals were detected by sight, or by capture in traps,
or were taken by shotgun with light shot. Trapped specimens were generally caught with smaller
museum special snap traps, larger rat traps, Macabee™ gopher traps, mole traps, or steel traps of
various sizes. They did not use a standardized protocol for trapping. Rather, they assessed the
potential species to be sampled and used the appropriate traps in suitable conditions. Grinnell et
al. typically recorded what types of traps were used, for how many nights, and what species were
caught on each night. Traplines were left out from 1-14 nights (mean for the west slope was 4.6
nights) and contained in average 24 mouse/rat traps (Table S1). For occupancy analyses we only
1
include captures from mouse and rat traps with recorded effort; captures based on specialized
trapping, such as gopher, mole, steel and tree traps, were excluded. Many specimens of more
common species were discarded, but are recorded as such in the field notes. Most animals that
were kept were preserved as study skin plus skull, but some were preserved as complete
skeletons or in formaldehyde.
For the resampling effort, it was not feasible to establish a standardized trapping design
for small mammals (e.g., grid or parallel lines of traps set at uniform distance intervals with a
common bait) given the diversity of habitats at each site, the differences in major habitats across
the elevational transect, and the range in food habits of focal taxa. Rather, we standardized trap
effort (number of traps and nights trapped) for each habitat. Each mammal live trap and pitfall
trap line at a site was “run” for a minimum of 4 consecutive days/nights. We used primarily
Sherman live traps, supplemented with Tomahawk live traps, with a minimum of 40 traps (40
Sherman live traps, sometimes supplemented with 10 Tomahawk live traps) per trapline per
night for the four consecutive nights. Traps were placed in “likely” spots within each habitat
(e.g., grass tunnels of Microtus). Pocket gophers were trapped using commercial Macabee™
gopher traps. Pitfall traps were used for shrews. Two meandering lines, each comprising of 25
32-oz. plastic cups, were placed in the ground at approximately 10 m intervals using a 10.2 cm
soil auger. These were run during the same trapping interval. The diversity of traps and methods
employed and habitats visited ensured that the full range of target taxa was sampled. For all our
analyses we only include captures from Sherman, Tomahawk, and pitfall cups in order to
maintain consistency with historical trapping methods.
Captured animals were identified, sexed, and weighed, with reproductive data noted for
most individuals. All trap lines or stations were georeferenced by hand-held GPS units, using the
WGS-84 datum. Data are archived in fieldnotes for all individuals encountered, including those
released as well as preserved. Voucher specimens of selected small mammals (rodents and
shrews) were taken in accordance with permission granted by the National Park Service and
Yosemite National Park. Specimens were archived in the collections of the Museum of
Vertebrate Zoology, as were those collected during the original Grinnell-era surveys. Data for all
specimens are available via the Museum’s website (http://mvz.berkeley.edu) under accession
numbers 13817 (2003), 13948 (2004), 14091 (2005), and 14191 (2006).
C. Data Set Construction
The trapping effort and elevational range of sampling was similar between the Grinnell
and contemporary periods. A total of 311 traplines where trapping effort could be quantified
were identified in Grinnell’s time and 308 in the resurvey. For both periods, traplines were
aggregated into sampling sites if they were within 2 km and 100 m elevation to reduce spatial
autocorrelation (Table S1). The higher level of aggregation in the Grinnell period reflects our
generally conservative approach to grouping traplines and greater uncertainty in the exact
location and elevation of traplines (mean point-radius error of georeference for historical
traplines was 323 ± 425.9 m). Accordingly, there was a larger number of both traplines (mean
2
4.8 vs 2.3) and traps (mean 111 vs 85) per site for the Grinnell period versus the re-survey.
However, the mean number of trap-nights per site was similar; 4.1 for Grinnell survey and 3.3
for the re-survey. Most, but not all, sites were geographically matched between the Grinnell and
re-survey periods.
Following aggregation, on the western slope of the transect there were 54 sites with
traplines in Grinnell’s time and 121 sites in the contemporary resurvey where trapping effort
could be quantified, spanning elevational ranges of 57–3287 masl in the original survey and 48–
3278 masl in the re-survey (Table S1). On the eastern slope there were 9 sites during Grinnell’s
time and 12 in the resurvey, spanning elevational ranges of 1981–2804 masl and 2155–3094
masl, respectively.
D. Estimation of the Probability of Detection, False Absence and Occupancy
We focus here on developing and comparing the elevational profiles of species
occupancy in order to maximize use of available data. In reporting the past and present
elevational ranges, we include additional observations and specimens for which effort was not
quantifiable (e.g., specimens shot in Grinnell surveys or observational data in both periods).
However, statistical analyses of detectability and occupancy across elevation are based solely on
the species and sites (as enumerated above) for which trap effort and nightly detection records
were quantified.
Although the overall survey methodology was similar between periods, differences in
trap types and effort per site could confound interpretation of absences and, thus, overall
comparisons. To control for these effects, we estimated detectability for each period and species
from the temporal pattern of presence or “no-presence” records across sites, and incorporated
any between-period difference in detectability into our analyses of changes in elevational range
limits and profiles of occupancy probability (ψ). Given prior evidence for distinct elevational
distributions of small mammals on the east versus west sides of the Sierra crest (S4), we used
only the west slope records to estimate parameters. The analyses of detectability and ψ employed
the likelihood framework and AIC model-averaging methods (S5) described in MacKenzie et al.
(S6) and implemented in Program MARK version 5.1 (S7).
To estimate the probability of detection per trap night (p), we constructed 32 competing
models with the following independent variables: era (Grinnell or resurvey), trend (linear decline
in detections over sequential nights due to the collection of trapped individuals or to trapshyness), trap effort (number of traps/100 and the log10 of the number of traps), the interaction
between era and trend, and the interactions between era and trap effort variables. We also built
detection models with all additive combinations of these independent variables, as well as a
constant model (.). The candidate model set is listed in Table S3.
We ran each p model with a ψera term and selected the best detection model with the
lowest AIC score for each species. We used the parameter values to estimate the overall
3
probability of detection (S6) as P* = 1 − ∏ (1 − pi ) for each site for each era based on its number
i
of nights trapped and traps used. To estimate the probability of false absence (Pfa) across a set of
sites in an elevational band where a species was detected in one era but not the other, we first
calculated the probability of a false absent for each site Pfa(site) = 1 − P(*site ) and then obtained the
product of these values across the set of sites in question as Pfa =
∏ (1 − P
fa ( site )
).
site
To estimate elevational profiles of occupancy (ψ) for each era, we again constructed a set
of competing likelihood models incorporating era (Grinnell or present), elevation represented as
linear (elev) or quadratic (elev + elev2) functions, and interactions between era and elevation
functions. This resulted in eight competing ψ models. Five models had between-era effects: era,
era+elev, era*elev, era+elev+ elev2, and era*(elev+ elev2). Three models had no era effects: elev,
elev+elev2, and constant (.). These are listed in Table S3 and illustrated in Figure S2.
The eight occupancy models were each run with a set of 14 detection functions that
included the best model for each species (Table S3). This resulted in a total of 112 models per
species in the occupancy model set. Models were compared using AICc (corrected for small
sample size) scores (S5). Occupancy profiles were estimated across the range of elevations
sampled by model-averaging ψ at 100-m increments using the AIC weights (w) of the 112
models. Occupancy-elevation profiles for each species appear in Fig. S3. Finally, cumulative
AIC weights were calculated for each occupancy model.
E. Estimation of Species Richness and Turnover
To estimate species richness and between-era turnover as a function of elevation, we
calculated species richness for the total transect, Yosemite National Park alone, and each of the 5
lifezones proposed by Grinnell, for each time period using presence/absence data from all the
mammals captured within these areas. The software EstimateS v. 8.0 was used to estimate
species richness metrics from replicated sample-based incidence data and between-era turnover
from similarity metrics (S8). This methodology allows controlling for different sampling efforts
at each time period. We calculated five non-parametric estimators of total species richness that
infer species not recorded: Incidence Coverage Estimator (ICE), Chao1, Chao2, Jack1, and Jack2
to estimate the asymptote of the species accumulation curve. Two similarity metrics that control
for effort and correct for unobserved species were estimated using replicated presence/absence
data, in practice, occurrence records across multiple sites within a lifezone, the Park, or the entire
transect: “Chao-Sorensen” and “Chao-Jaccard” each estimate the probability of choosing two
individuals, one from each of the two samples, which belong to a species shared between the
samples (S9, S10). Following Wilson et al. (S11), we report the mean and standard error across
the five non-parametric estimators of total richness and the two similarity indices (Table S4).
Individual estimators follow the same trends and they are shown in Figure S4. To test the
hypothesis of a change in species richness between the two time periods we employed a
4
repeated-measures one-way ANOVA with time as a factor and lifezones as the subjects on which
repeated measures were taken.
5
Figure S1. Changes in minimum and maximum temperatures in Yosemite Valley (WRCC049855 37°45' 119°35' 1250 msnm) over the past 100 years. Source data from Western
Regional Climate Center (WRCC: http://www.wrcc.dri.edu).
6
Figure S2. Eight occupancy models tested for each small mammal species with sufficient
quantitative trapping data for analysis.
7
Figure S3. Comparison of elevation profiles for 28 species and occupancy results for 23 species
of small mammals of the YNP transect in Table 1. Elevation plots are shown separately for the
western and eastern slopes of the transect across the Sierra Nevada. Displayed are occupied
(black) and unoccupied (grey) sites, results from the probability of false absence (Pfa) tests, and
cumulative AIC weights and model-averaged occupancy-elevation profiles for historic (black)
and modern (red) based on 112 models (Table S3, Fig. S2) averaged using the AIC weights. Red
(historic) and green (modern) circles refer to ad hoc records of occurrence based on specimens
collected or observed that were not part of the quantitative trapping effort.
8
1. Microtus californicus
Occupancy models
Constant
Elev
2
Elev+Elev
Elev
Elev
Era
2
Era*(Elev + Elev )
Era*Elev
Era+Elev
2
Era+Elev+Elev
+505m
13 sites
Pfa < 0.001
Cumulative AIC Wt
0.00
0.36
0.08
0.00
0.01
0.11
0.33
0.11
O
ccupancy
0. 9
0. 8
0. 7
0. 6
0. 5
0. 4
0. 3
0. 2
0. 1
0. 0
0
1000
2000
3000
El evat i on
Moritz et al.
Er a
Hi st or i ca
M
oder n
4000
2. Reithrodontomys megalotis
Occupancy models
Constant
Elev
2
Elev+Elev
Era
2
Era*(Elev + Elev )
Era*Elev
Era+Elev
2
E El
Era+Elev+Elev
El
Cumulative AIC Wt
0.00
0.50
0 6
0.16
0.00
0.01
0.09
0.18
0 06
0.06
O
ccupancy
1. 0
0. 9
+ 112m
9 sites
Pfa <0.001
0. 8
0. 7
0. 6
0. 5
0. 4
0. 3
0. 2
0. 1
0. 0
0
1000
2000
3000
El evat i on
Er a
Moritz et al.
Hi st or i ca
M
oder n
4000
3. Peromyscus truei
Occupancy models
Constant
Elev
2
Elev+Elev
Era
2
Era*(Elev + Elev )
Era*Elev
Era+Elev
2
Era+Elev+Elev
Colonization from E. side
+ 589m
9 sites
Pfa <0.001
+ 486m
5 sites
Pfa < 0.001
Moritz et al.
Cumulative AIC Wt
0.00
0.00
0.00
0.00
0.99
0.00
0.00
0.00
4. Chaetodipus californicus
Occupancy models
Constant
Elev
2
Elev+Elev
Era
2
Era*(Elev + Elev )
Era*Elev
Era+Elev
2
Era+Elev+Elev
Cumulative AIC Wt
0.00
0.01
0.01
0.00
0.32
0.24
0 22
0.22
0.20
O
ccupancy
1. 0
0. 9
0. 8
0. 7
0. 6
+ 800m
17 sites
Pfa = 0.005
+ 385m
5 sites
Pfa = 0.24
0. 5
0. 4
0. 3
0. 2
0. 1
0. 0
0
1000
2000
3000
El evat i on
Er a
Moritz et al.
Hi st or i ca
M
oder n
4000
5. Sorex ornatus
Occupancy models
Constant
Elev
2
Elev+Elev
Era
2
Era*(Elev + Elev )
Era*Elev
Era+Elev
2
Era+Elev+Elev
-370m
10 sites
-482m
Pfa = 0
0.10
10
8 sites
Pfa = 0.01
Moritz et al.
Cumulative AIC Wt
0.00
0.02
0.03
0.00
0.74
0.02
0 02
0.02
0.17
6. Sorex monticolus
+85m
Occupancy models
Constant
Elev
2
El +El
Elev+Elev
Era
2
Era*(Elev + Elev )
Era*Elev
Era+Elev
2
Era+Elev+Elev
Cumulative AIC Wt
0.00
0.00
0 00
0.00
0.00
0.28
0.08
0.25
0.37
3 sites
-1003m
Pfa < 0.001
40 sites
Pfa <0.001
O
ccupancy
1. 0
0. 9
0. 8
0. 7
0. 6
0. 5
0. 4
0. 3
0. 2
0. 1
0. 0
0
Moritz et al.
1000
2000
3000
El evat i on
Er a
Hi st or i ca
M
oder n
4000
7. Dipodomys
p
y heermanni
Occupancy models
Constant
Elev
2
Elev+Elev
Era
2
Era*(Elev + Elev )
Era*Elev
Era+Elev
2
Era+Elev+Elev
Cumulative AIC Wt
0.00
0 04
0.04
0.12
0.00
0.04
0.48
0.03
0.28
O
ccupancy
0. 9
- 293m
0. 8
0. 7
6 Sites
Pfa <0.001
0. 6
0. 5
0. 4
+ 63m
0. 3
6 Sites
0. 2
Pfa <0.001
0. 1
0. 0
0
1000
2000
3000
El evat i on
Moritz et al.
Er a
Hi st or i ca
M
oder n
4000
8. Microtus longicaudus
g
Occupancy models
Constant
Elev
2
Elev+Elev
Era
2
Era*(Elev + Elev )
Era*Elev
Era+Elev
2
Era+Elev+Elev
Cumulative AIC Wt
0.00
0.00
0 00
0.00
0.00
0.19
0.03
0.04
0.74
O
ccupancy
1. 0
0. 9
0. 8
+ 614m
22 sites
Pfa<0.001
0. 7
0. 6
0 5
0.
0. 4
0. 3
0. 2
0. 1
0. 0
0
1000
Moritz et al.
2000
3000
El evat i on
Er a
Hi st or i ca
M
oder n
4000
9. Zapus princeps
Occupancy models
Constant
Elev
2
Elev+Elev
Era
2
Era*(Elev + Elev )
Era*Elev
Era+Elev
2
Era+Elev+Elev
-64m
5 sites
Pfa <0.001
+ 159m
(No change)
Cumulative AIC Wt
0.00
0.03
0 35
0.35
0.00
0.06
0.01
0.02
0.53
O
ccupancy
0. 7
10 sites
0. 6
Pfa < 0.001
0. 5
0 4
0.
0. 3
0. 2
0. 1
0. 0
Moritz et al.
0
1000
2000
3000
El evat i on
Er a
Hi st or i ca
M
oder n
4000
10. Tamias senex
-334m
13 sites
Pfa <0.001
0.001
Occupancy models
Constant
Elev
2
Elev+Elev
Era
2
Era*(Elev + Elev )
Era*Elev
Era+Elev
2
Era+Elev+Elev
Cumulative AIC Wt
0.00
0.00
0.48
0.00
0.19
0.00
0 00
0.00
0.33
+ 1007m
61 sites
Pfa <0.001
O
ccupancy
1. 0
0. 9
0. 8
0. 7
Modern occupancy model unstable;
collapsed to only at single site
0. 6
0. 5
0. 4
0. 3
0. 2
0 1
0.
0. 0
0
Moritz et al.
1000
2000
3000
El evat i on
Er a
Hi st or i ca
M
oder n
4000
11. Spermophilus lateralis
Occupancy models
Constant
Elev
2
Elev+Elev
Era
2
Era*(Elev + Elev )
Era*Elev
Era+Elev
2
Era+Elev+Elev
Cumulative AIC Wt
0.00
0.00
0.00
0.00
0.78
0.10
0 01
0.01
0.11
+ 244m
7 sites
Pfa <0
<0.001
001
O
ccupancy
1. 0
0. 9
0. 8
0. 7
0. 6
0. 5
0. 4
0. 3
0. 2
0. 1
0. 0
0
Moritz et al.
1000
2000
3000
El evat i on
Er a
Hi st or i ca
M
oder n
4000
12. Sorex palustris
Absent
9 sites
+ 512m
Occupancy models
Constant
Elev
2
Elev+Elev
Era
2
Era*(Elev + Elev )
Era*Elev
Era+Elev
2
Era+Elev+Elev
Cumulative AIC Wt
0.00
0.00
0 00
0.00
0.00
0.12
0.14
0.34
0.39
Pfa = 0.32
O
ccupancy
1. 0
20 sites
0. 9
Pfa = 0.012
0. 8
0. 7
0. 6
0. 5
0. 4
0. 3
0. 2
0. 1
0. 0
0
1000
2000
3000
El evat i on
Er a
Moritz et al.
Hi st or i ca
M
oder n
4000
13. Neotoma cinerea
- 791m
32 sites
Pfa<
0.0001
+ 609m
35 sites
Pfa<
0.0001
- 339m
339
2 sites
Pfa = 0.09
+ 406m
Occupancy models
Constant
Elev
2
Elev+Elev
Elev
Elev
Era
2
Era*(Elev + Elev )
Era*Elev
Era+Elev
2
Era+Elev+Elev
Cumulative AIC Wt
0.00
0.02
0.02
0.00
0.83
0.02
0.01
0 10
0.10
6 sites
Pfa < 0.001
O
ccupancy
0. 8
0. 7
0. 6
0. 5
0. 4
0. 3
0. 2
0. 1
0. 0
Moritz et al.
0
1000
2000
3000
El evat i on
Er a
Hi st or i ca
M
oder n
4000
14. Spermophilus beldingi
+ 939m
+ 355m
11 sites
20 sites
Pfa < 0.001
Pfa < 0.001
Occupancy models
Constant
Elev
2
Elev+Elev
Era
2
Era*(Elev + Elev )
Era*Elev
Era+Elev
2
Era+Elev+Elev
Cumulative AIC Wt
0.00
0 32
0.32
0.22
0.00
0.02
0.13
0.20
0.11
O
ccupancy
0. 8
0. 7
0. 6
0. 5
0. 4
0. 3
0. 2
0. 1
0. 0
Moritz et al.
0
1000
2000
3000
El evat i on
Er a
Hi st or i ca
M
oder n
4000
15. Tamias alpinus
Absent
+ 629m
•Sites
Occupancy models
Constant
Elev
2
Elev+Elev
Era
2
Era*(Elev + Elev )
Era*Elev
Era+Elev
2
Era+Elev+Elev
Cumulative AIC Wt
0.00
0.00
0.00
0.00
0.06
0.19
0 56
0.56
0.18
•P<0.001
O
ccupancy
1. 0
0. 9
0. 8
0. 7
0. 6
0. 5
0. 4
0. 3
0. 2
0. 1
0. 0
0
1000
2000
3000
El evat i on
Er a
Moritz et al.
Hi st or i ca
M
oder n
4000
16. Ochotona princeps
+350m
4 sites
+153 m
6 sites
Moritz et al.
Data insufficient to
analyze with occupancy
models.
17. Peromyscus maniculatus
Occupancy models
Constant
Elev
2
Elev+Elev
Era
2
Era*(Elev + Elev )
Era*Elev
Era+Elev
2
Era+Elev+Elev
Cumulative AIC Wt
0.00
0.00
0 01
0.01
0.00
0.72
0.00
0.00
0.26
O
ccupancy
1. 0
0. 9
0. 8
0. 7
0. 6
0. 5
0
0. 4
Moritz et al.
0
1000
2000
3000
El evat i on
Er a
Hi st or i ca
M
oder n
4000
18. Thomomys bottae
Nonstandard trapping technique
made data unsuitable for
use with occupancy models.
Moritz et al.
19. Spermophilus beecheyi
-250m
Absent
10 sites
5 sites
Pfa <0.001
Pfa = 0.21
Occupancy models
Constant
Elev
2
Elev+Elev
Era
2
Era*(Elev + Elev )
Era*Elev
Era+Elev
2
Era+Elev+Elev
Cumulative AIC Wt
0.00
0.00
0.03
0.00
0.89
0.01
0 00
0.00
0.07
O
ccupancy
1. 0
0. 9
0. 8
0. 7
0. 6
0. 5
0. 4
0. 3
0. 2
0. 1
0. 0
0
1000
Moritz et al.
2000
3000
El evat i on
Er a
Hi st or i ca
M
oder n
4000
20. Neotoma macrotis
Occupancy models
Constant
Elev
2
Elev+Elev
Era
2
Era*(Elev + Elev )
Era*Elev
E El
Era+Elev
2
Era+Elev+Elev
Cumulative AIC Wt
0.00
0.03
0.62
0.00
0.10
0.01
0 03
0.03
0.21
+ 67m
P* = 0
P
0,02
02
O
ccupancy
0. 8
0. 7
0. 6
0. 5
0. 4
0. 3
0. 2
0. 1
0. 0
0
1000
2000
3000
El evat i on
Er a
Moritz et al.
Hi st or i ca
M
oder n
4000
21. Peromyscus boylii
Occupancy models
Constant
Elev
2
Elev+Elev
Elev
Elev
Era
2
Era*(Elev + Elev )
Era*Elev
Era+Elev
2
Era+Elev+Elev
Cumulative AIC Wt
0.00
0.00
0.60
0.00
0.08
0.00
0.00
0.32
O
ccupancy
0. 7
0. 6
0. 5
0. 4
0. 3
-122m
2 sites
P<0.001
0. 2
0. 1
0. 0
0
1000
2000
3000
El evat i on
Moritz et al.
Er a
Hi st or i ca
M
oder n
4000
22. Sorex trowbridgii
Occupancy models
Constant
Elev
2
Elev+Elev
Era
2
Era*(Elev + Elev )
Era*Elev
E El
Era+Elev
2
Era+Elev+Elev
Cumulative AIC Wt
0.00
0.00
0.40
0.00
0.21
0.00
0 00
0.00
0.39
O
ccupancy
0. 6
0. 5
0. 4
0. 3
0. 2
0. 1
0. 0
0
Moritz et al.
1000
2000
3000
El evat i on
Er a
Hi st or i ca
M
oder n
4000
23. Microtus montanus
Occupancy models
Constant
Elev
2
Elev+Elev
Era
2
Era*(Elev + Elev )
Era*Elev
Era+Elev
2
Era+Elev+Elev
Cumulative AIC Wt
0.01
0.14
0 36
0.36
0.01
0.04
0.06
0.11
0.28
O
ccupancy
0. 46
0. 44
0. 42
0. 40
0. 38
0. 36
0. 34
0. 32
0. 30
0. 28
0. 26
0. 24
0. 22
0. 20
0. 18
0. 16
0. 14
0. 12
0. 10
0. 08
0. 06
0. 04
Moritz et al.
0
1000
2000
3000
El evat i on
Er a
Hi st or i ca
M
oder n
4000
24. Tamiasciurus douglasi
Data insufficient to
analyze with occupancy
models as only one capture
occurred at each site
site.
Moritz et al.
25. Tamias quadrimaculatus
+ 50m
2 sites
Occupancy models
Constant
Elev
2
Elev+Elev
Era
2
Era*(Elev + Elev )
Era*Elev
Era+Elev
2
Era+Elev+Elev
Cumulative AIC Wt
0.00
0 00
0.00
0.16
0.00
0.78
0.00
0.00
0.07
Pfa = 0,002
O
ccupancy
1. 0
0. 9
0. 8
0. 7
0. 6
0. 5
0. 4
0. 3
0. 2
0. 1
0. 0
0
Moritz et al.
1000
2000
3000
El evat i on
Er a
Hi st or i ca
M
oder n
4000
26. Tamias speciosus
p
Occupancy models
Constant
Elev
2
Elev+Elev
Era
2
Era*(Elev + Elev )
Era*Elev
Era+Elev
2
Era+Elev+Elev
+ 65m
2 sites
Pfa <0.001
Cumulative AIC Wt
0.00
0 00
0.00
0.00
0.00
1.00
0.00
0.00
0.00
+ 128m
3 sites
O
ccupancy
1. 0
0. 9
Pfa <0.001
0. 8
0. 7
0. 6
0. 5
0. 4
0. 3
0. 2
0. 1
0. 0
0
1000
2000
3000
El evat i on
Moritz et al.
Er a
Hi st or i ca
M
oder n
4000
27. Thomomys monticola
Nonstandard trapping techniques
made data unsuitable for use
with occupancy models.
Moritz et al.
28. Marmota flaviventris
Nonstandard observation-based
records made data unsuitable
for use with occupancy models.
Moritz et al.
Supporting Online Material
Moritz et al.
Figure S4 – Species richness estimators (+1 SD) by era for each lifezone, Yosemite National
Park (Park) and the entire transect (Park&Transect). The five non-parametric estimators of total
species richness are Chao1, Chao2, Incidence Coverage Estimator (ICE), Jack1, and Jack2 to
estimate the asymptote of the species accumulation curve.
37
Supporting Online Material
Moritz et al.
38
Supporting Online Material
Moritz et al.
Figure S5. Probability of an upper limit range expansion for 10 low-mid elevation species in
relation to longevity (life span in years) and litters per year derived from the best two composite
posthoc logistic regression models (Life zone, Longevity; Life zone, Litters per year) in Table S5
based on an information theoretic approach to model selection. Life history data shown in Table
S6. No mid-high species exhibited upwards range shifts, and the modeled probability of an
Probability of an upwards shift
upwards range expansion in relation to longevity and litter size was near zero.
1.0
0.8
LITTERS
0.6
0.4
0.2
LONGEVITY
0.0
0
1
2
3
4
5
6
Litters per year or years of life
39
Supporting Online Material
Moritz et al.
Figure S6 – Examples of photographic retakes illustrating precise location of historic sampling
units and similarity of habitat.
40
Supporting Online Material
Moritz et al.
.
Table S1. Details of effort and location for trapping sites. Elevation (Elev.), latitude and
longitude refer to centroids for traplines, aggregated as described under Methods. Under
Lifezone, USon, LAon and Huds-Alp refer to “Upper Sonoran”, “Lower Sonoran”, and
“Hudsonian-Alpine”, respectively. Trap effort is the product of average number of nights
trapped (Av. No. Nights) and the average number of traps per night.
Period
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Historic
Site
La Grange-2
La Grange-1
Pleasant Valley-5
Pleasant Valley-1
Pleasant Valley-2
Pleasant Valley-3
Pleasant Valley-4
Coulterville-1
El Portal-5
Mt Bullion-1
El Portal-4
El Portal-1
Coulterville-3
Coulterville-2
El Portal-3
Happy Isles-1
Cascade Creek-1
Cascade-1
Merced Grove-1
Coulterville-4
Gentrys-1
Chinquapin-1
Aspen Valley-1
Crane Flat-1
Mono PO-1
Dry Creek-1
Farrington-1
Mono Meadow-1
Mono Craters-1
Mono Mills-1
Merced Lake-1
Indian Canyon-1
Glen Aulin-1
Merced Lake-2
Mono Craters-2
Gem Lake-1
Lyell Canyon-1
Lyell Canyon-2
No. of
Traplines
1
5
6
12
6
2
3
2
1
1
4
14
3
8
1
1
1
3
12
3
5
7
3
2
8
2
5
6
1
2
9
8
7
1
2
2
6
1
Slope
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
E
E
E
W
E
E
W
W
W
W
E
E
W
W
41
Lifezone
Lson
Lson
Uson
Lson
Uson
Lson
Lson
Uson
Uson
Uson
Uson
Uson
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Canadian
Canadian
Canadian
Huds-Alp
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Huds-Alp
Huds-Alp
Huds-Alp
Elev.
(masl)
57
69
274
277
277
277
288
500
593
676
697
742
916
1043
1153
1285
1444
1444
1679
1705
1822
1865
1946
1956
1958
2078
2092
2176
2244
2244
2266
2357
2455
2503
2684
2824
2966
3099
Av. No.
Nights
3.0
8.3
5.9
4.6
3.9
2.4
2.3
2.0
4.0
2.0
6.3
6.7
1.3
5.9
2.0
3.0
4.0
3.7
4.5
5.5
3.4
4.3
4.7
1.0
2.5
1.0
5.8
5.3
1.0
2.3
6.0
3.1
5.0
1.0
1.0
1.0
5.1
7.0
Trap
Effort
15
440
452
1425
360
386
62
271
60
40
923
2897
75
1389
44
102
148
230
1001
204
524
835
544
20
244
102
457
825
1
275
1257
696
725
12
150
21
917
189
Latitude
37.666
37.666
37.660
37.659
37.659
37.659
37.659
37.711
37.674
37.508
37.665
37.674
37.754
37.743
37.688
37.732
37.728
37.726
37.748
37.748
37.735
37.652
37.830
37.758
37.991
37.935
37.905
37.657
37.888
37.888
37.740
37.779
37.917
37.743
37.864
37.750
37.777
37.774
Longitude
-120.470
-120.470
-120.275
-120.287
-120.287
-120.287
-120.287
-120.215
-119.781
-120.044
-119.807
-119.781
-120.106
-120.157
-119.764
-119.561
-119.712
-119.711
-119.835
-119.835
-119.703
-119.703
-119.773
-119.798
-119.141
-118.935
-119.102
-119.597
-118.960
-118.960
-119.397
-119.566
-119.440
-119.388
-119.006
-119.148
-119.261
-119.260
Supporting Online Material
Historic
Historic
Historic
Historic
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Lyell Canyon-5
Mt Hoffman-1
Lyell Canyon-3
Lyell Canyon-4
LG-1
LG-2
LG-4
LG-3
LG-5
S-1
LG-6
S-3
S-4
CPV-11
CPV-8
CPV-13
CPV-4
CPV-7
CPV-3
CPV-2
CPV-1
CPV-6
CPV-10
CPV-5
CPV-14
MD-2
MD-1
CPV-12
Ca-1
FM-2
YV-7
YV-10
YV-2
YV-6
YV-8
YV-1
YV-5
YV-11
YV-3
YV-4
YV-12
YV-13
FM-1
YV-9
F-1
HM-1
MG-1
HG-1
HG-2
Moritz et al.
2
3
4
3
1
2
2
2
2
2
1
2
3
1
2
1
1
4
1
1
1
1
1
1
2
1
2
1
3
4
1
2
2
2
3
4
2
1
3
5
1
2
2
1
1
2
5
2
1
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Lson
Lson
Lson
Lson
Lson
Lson
Lson
Lson
Lson
Uson
Uson
Uson
Uson
Uson
Uson
Uson
Uson
Uson
Uson
Uson
Uson
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
42
3099
3137
3201
3275
48
51
61
62
68
87
94
117
119
282
498
544
544
595
669
732
794
844
850
852
881
901
902
914
1051
1140
1209
1211
1212
1216
1219
1223
1225
1228
1233
1236
1237
1269
1272
1330
1392
1428
1672
1689
1713
3.5
1.4
3.6
8.0
4.0
1.0
3.0
3.0
4.0
5.0
3.0
3.0
3.7
4.0
3.5
4.0
4.0
3.0
4.0
4.0
4.0
2.0
3.0
3.0
3.0
2.0
4.5
3.0
2.3
3.3
4.0
2.0
3.0
4.0
3.0
4.3
5.0
3.0
4.0
2.2
3.0
3.0
3.0
2.0
2.0
4.0
3.4
3.0
4.0
178
90
160
307
80
60
240
240
320
400
120
240
610
160
191
480
240
223
80
160
80
40
30
180
200
40
480
240
460
472
335
130
150
260
234
560
400
150
420
145
240
220
210
80
80
520
940
192
250
37.773
37.844
37.770
37.764
37.625
37.622
37.666
37.664
37.669
37.511
37.674
37.529
37.547
37.709
37.723
37.720
37.656
37.724
37.647
37.640
37.634
37.610
37.739
37.619
37.736
37.755
37.756
37.684
37.723
37.579
37.741
37.746
37.722
37.738
37.561
37.715
37.731
37.741
37.731
37.732
37.733
37.753
37.566
37.752
37.705
37.796
37.748
37.767
37.763
-119.263
-119.506
-119.257
-119.251
-120.567
-120.526
-120.463
-120.479
-120.462
-120.384
-120.466
-120.351
-120.355
-120.221
-120.268
-120.179
-120.221
-120.260
-120.211
-120.217
-120.207
-120.178
-120.248
-120.187
-120.166
-120.075
-120.090
-120.121
-119.712
-119.882
-119.594
-119.579
-119.636
-119.605
-119.591
-119.665
-119.603
-119.572
-119.614
-119.608
-119.558
-119.546
-119.869
-119.587
-119.733
-119.868
-119.839
-119.865
-119.860
Supporting Online Material
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
MG-2
Ch-1
AV-1
Ch-2
CF-2
CF-4
CF-3
CF-1
Ch-3
TF-1
TF-2
CF-5
MMe-5
MMe-7
MMe-4
WB-1
MMe-3
IC-2
MoMe-1
MoMe-2
TC-1
WB-2
ML-5
BC-1
ML-4
MMe-2
WC-1
ML-3
ML-2
MMi-1
SM-1
SM-2
ML-1
YC-1
IC-1
MMe-1
GA-4
GA-5
WW-3
WW-5
GA-2
WW-6
WW-1
WL-1
SL-1
WL-2
WW-2
PF-1
WW-4
Moritz et al.
1
1
3
2
11
3
8
1
1
1
1
2
3
2
1
2
1
2
1
1
1
2
4
6
2
2
2
4
3
1
1
1
1
3
1
2
3
2
1
1
4
1
3
2
1
1
1
3
1
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
E
W
W
W
W
W
E
W
E
W
W
E
W
W
E
W
W
W
W
W
W
W
W
W
W
W
W
W
E
W
E
W
W
W
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Transition
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
43
1809
1835
1872
1877
1896
1899
1902
1951
1972
2013
2013
2106
2140
2143
2151
2155
2160
2164
2170
2170
2191
2195
2199
2214
2224
2224
2236
2241
2246
2251
2253
2258
2261
2296
2306
2350
2389
2389
2397
2397
2405
2409
2415
2440
2446
2465
2484
2486
2489
2.0
4.0
3.0
2.5
3.4
4.0
4.6
2.0
1.0
2.0
2.0
3.0
3.3
4.5
4.0
3.0
4.0
3.0
3.0
4.0
4.0
1.0
3.0
4.5
2.5
4.0
2.0
3.3
3.3
2.0
4.0
4.0
3.0
3.3
4.0
3.5
3.7
4.0
2.0
2.0
2.5
6.0
4.3
4.0
2.0
4.0
4.0
4.0
2.0
80
440
405
64
1199
335
967
80
40
80
20
200
440
445
320
272
320
70
12
320
160
120
365
771
170
400
136
385
280
100
160
80
120
430
160
240
454
338
160
80
464
60
815
475
80
236
320
580
160
37.762
37.648
37.825
37.652
37.757
37.746
37.751
37.753
37.671
37.755
37.755
37.758
37.665
37.670
37.662
37.908
37.668
37.774
37.666
37.666
37.811
37.908
37.740
37.900
37.739
37.670
37.897
37.739
37.732
37.888
37.676
37.672
37.721
37.850
37.780
37.699
37.914
37.912
37.845
37.846
37.913
37.839
37.868
37.871
37.851
37.871
37.857
37.807
37.843
-119.843
-119.704
-119.772
-119.700
-119.802
-119.799
-119.794
-119.809
-119.684
-119.743
-119.743
-119.770
-119.622
-119.625
-119.601
-119.116
-119.597
-119.569
-119.668
-119.668
-119.713
-119.128
-119.410
-119.130
-119.402
-119.585
-119.130
-119.396
-119.394
-118.960
-119.652
-119.657
-119.395
-119.576
-119.564
-119.586
-119.429
-119.425
-119.613
-119.633
-119.421
-119.593
-119.648
-119.171
-119.659
-119.161
-119.647
-119.564
-119.623
Supporting Online Material
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
Current
GA-3
GA-1
McS-1
FD-1
SC-1
PF-2
JR-1
SN-1
GM-1
WF-2
WF-1
LM-1
TL-1
DeM-1
DL-1
KM-2
TL-2
KM-1
MF-1
DD-1
LC-1
LC-2
V-2
RC-1
V-1
WF-3
LC-3
V-4
WF-4
V-5
LC-4
TP-1
V-3
V-6
V-8
V-7
LC-5
LC-7
LC-6
Moritz et al.
1
3
2
1
1
1
1
1
2
2
1
1
1
1
4
6
1
1
1
1
3
4
2
6
1
3
1
2
1
2
13
1
4
3
1
1
4
1
1
W
W
W
W
W
W
W
W
W
E
E
W
W
W
W
W
W
E
W
W
W
W
W
W
W
E
W
W
E
W
W
W
W
W
W
W
W
W
W
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Canadian
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
Huds-Alp
44
2492
2496
2508
2556
2571
2572
2641
2655
2761
2787
2800
2823
2828
2868
2874
2883
2936
2941
2941
2968
2983
2983
3015
3018
3024
3040
3051
3073
3094
3107
3121
3149
3149
3159
3167
3184
3220
3264
3278
3.0
2.7
3.0
3.0
4.0
4.0
3.0
4.0
3.0
4.5
4.0
4.0
4.0
2.0
4.5
5.7
4.0
4.0
3.0
2.0
4.0
3.0
3.5
5.3
3.0
3.0
5.0
3.0
3.0
4.0
3.8
2.0
3.0
3.3
3.0
2.0
3.3
3.0
3.0
72
416
315
240
160
40
240
160
150
275
160
240
120
42
592
1394
176
160
180
118
292
459
140
1471
120
270
120
240
240
240
1710
80
472
317
120
72
610
120
240
37.916
37.902
37.852
37.876
37.818
37.814
37.884
37.826
38.163
37.954
37.954
37.883
37.905
37.899
38.173
38.122
37.904
38.130
37.841
37.908
37.780
37.778
37.790
38.061
37.798
37.953
37.772
37.800
37.963
37.797
37.768
37.908
37.788
37.797
37.805
37.791
37.764
37.757
37.765
-119.418
-119.431
-119.628
-119.416
-119.510
-119.577
-119.363
-119.499
-119.605
-119.229
-119.226
-119.347
-119.532
-119.348
-119.595
-119.483
-119.535
-119.479
-119.500
-119.348
-119.261
-119.261
-119.352
-119.339
-119.349
-119.262
-119.258
-119.342
-119.272
-119.339
-119.255
-119.264
-119.344
-119.336
-119.328
-119.328
-119.260
-119.259
-119.252
Supporting Online Material
Moritz et al.
Table S2. Small mammal species included in analyses. Slope is east (E) or west (W), with
first records marked as *. Method refers to standardized trapping (S), observation (O) or
special trapping (Sp). Species included in richness analyses are listed as occurring (1) for
Grinnell (G) and Present (P) surveys for the whole transect, and for Yosemite National
Park alone. Species included in analyses of range limits are listed as having appropriate
data for occupancy modeling (Y) or not (N). We observed all 42 of the focal taxa
observed in the Grinnell period, and one new species, Sorex tenellus, a rare shrew
encountered at two high elevation sites (ca. 3020 m) that previously was known from
mid-high elevations to the north and east. We encountered two species (Spermophilus
beecheyi and Peromyscus boylii) new to the east side of the transect. Within YNP, we
detected all 27 species observed in Grinnell’s time and three new ones – Sorex tenellus,
Chaetodipus californicus, and Reithrodontomys megalotis. The last two resulted from
upward range expansions.
Species
Chaetodipus californicus
Dipodomys heermanni
Dipodomys panamintinus
Glaucomys sabrinus
Lemmiscus curtatus
Marmota flaviventris
Microtus californicus
Microtus longicaudus
Microtus montanus
Neotoma cinerea
Neotoma macrotis
Ochotona princeps
Onychomys leucogaster
Perognathus inornatus
Perognathus parvus
Peromyscus boylii
Peromyscus californicus
Peromyscus maniculatus
Peromyscus truei
Phenacomys intermedius
Reithrodontomys megalotis
Sorex lyelli
Sorex monticolus
Sorex ornatus
Sorex palustris
Sorex tenellus
Sorex trowbridgii
Sorex vagrans
Spermophilus beecheyi
Slope
W
W
E
W
E
E, W
W
E, W
E, W
E, W
W
E, W
E
W
E
E*, W
W
E, W
E, W
W
W
E, W
E, W
W
E, W
W*
W
E
E*, W
Method
S
S
S
S
S
O
S
S
S
S
S
O
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
45
Richness
Transect
YNP
G
P
G
P
1
1
0
1
1
1
0
0
1
1
0
0
1
1
1
1
1
1
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
0
1
1
0
0
1
1
0
0
1
1
1
1
1
1
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
1
1
1
1
1
1
1
1
1
1
1
0
0
1
1
1
1
0
1
0
1
1
1
1
1
1
1
0
0
1
1
1
1
Range limits
Occupancy
Y
Y
N
Y
Y
Y
Y
Y
N
Y
Y
Y
Y
Y
Y
Y
Y
Supporting Online Material
Spermophilus beldingi
Spermophilus lateralis
Tamias alpinus
Tamias amoenus
Tamias merriami
Tamias minimus
Tamias quadrimaculatus
Tamias senex
Tamias speciosus
Tamiasciurus douglasii
Thomomys bottae
Thomomys monticola
Thomomys talpoides
Zapus princeps
Total
Moritz et al.
E, W
E, W
E, W
E
W
E
W
W
E, W
E, W
W
E, W
E
E, W
S
S
S
S
S
S
S
S
S
O
Sp
Sp
Sp
S
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
0
0
1
1
1
1
1
1
0
1
1
1
1
0
0
0
1
1
1
1
1
1
0
1
Y
Y
Y
Y
Y
Y
Y
N
N
N
Y
43
42
43
27
30
28
46
Supporting Online Material
Moritz et al.
Table S3. Candidate model sets for the occupancy analysis. Initially we screened 36
detection models for each small mammal species in the Yosemite transect with trapping
data combined from both the west and east slopes. This model set was then reduced to 14
detection models in the final set ( = x) that incorporated either the best (lowest AICc) or
near best models for each species. The 8 occupancy models were each run with the final
set of 14 detection functions yielding 112 models.
Model parameter
Detection
Model terms
constant (.)
era
era + era*log(traps)
era + era*log(traps) + era*traps/100
era + era*log(traps) + era*traps/100 +
era*trend
era + era*log(traps) + era*trend
era + era*log(traps) + traps/100
era + era*traps/100
era + era*traps/100 + era*trend
era + era*trend
era + log(traps)
era + log(traps) + era*traps/100
era + log(traps) + era*trend
era + log(traps) + traps/100 + trend
era + traps/100
era + traps/100 + era*trend
era + traps/100 + trend
era + trend
era + trend + era*log(traps)
era + trend + era*traps/100
era + log(traps) + trend
era*log(traps) + era*traps/100
era*log(traps) + era*traps/100 + era*trend
era*log(traps) + era*trend
era*traps/100 + era*trend
log(traps)
log(traps) + era*traps/100
log(traps) + era*trend
log(traps) + trend
traps/100
traps/100 + era*log(traps)
traps/100 + era*trend
traps/100 + trend
47
Final set
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Supporting Online Material
Occupancy
Moritz et al.
trend
trend + era*log(traps)
trend + era*traps/100
constant (.)
elevation
x
x
x
elevation + elevation2
era
era + elevation
x
x
x
era + elevation + elevation2
era * elevation
x
x
era * (elev+ elev2)
x
48
Supporting Online Material
Moritz et al.
Table S4. Summary of mean and standard errors of estimates of species richness by
sampling period and similarity of species assemblages between periods (see Methods).
Also shown is the difference in estimated species richness between Current and Historical
sampling periods as absolute numbers (C - H) and percent (%) change.
Richness
___Current__
Historical
Difference
Location
Mean
SE
Mean
SE
C-H
Transect
44.12
1.88
48.54
2.53
Park
30.47
1.44
29.16
Low Sonoran
10.66
0.81
Upper Sonoran
11.31
Transition
Similarity
%
Mean
SE
-4.42
-9.11
1.00
0.00
1.39
1.31
4.49
1.00
0.00
15.47
1.83
-4.82
-31.12
0.92
0.03
0.98
15.79
1.26
-4.48
-28.35
0.92
0.04
21.93
0.86
26.22
1.52
-4.29
-16.36
0.86
0.06
Canadian
17.41
1.40
19.92
1.05
-2.52
-12.64
0.97
0.01
Hudsonian-Arctic
17.46
0.73
19.11
0.78
-1.65
-8.62
0.88
0.05
49
Supporting Online Material
Moritz et al.
Table S5. Information theoretic approach to model selection for logistic regression
models relating mammal life history traits (Table S6) to the probability of an upward shift
in the lower or upper limit of elevational range for 28 small mammal species. K is the
number of parameters, AICc is the Akaike’s Information Criterion corrected for small
sample size, ∆AICc is the difference between the model and the best (lowest AIC) model,
and AIC weight (w) indicates the relative explanatory ability of a model compared to
others in the same model set. Post hoc models are given for the best single model
combined with every other parameter. Higher order models were not supported by small
samples sizes.
Lower Limit Range Change Models
Life zone
Constant (.)
Litters per year
Young per year
Mass
Litter size
Longevity
Annual rhythm
Daily rhythm
Diet
K
2
1
2
2
2
2
2
3
3
4
AICc
35.93
38.65
39.84
40.04
40.41
40.78
40.81
41.18
41.85
45.01
∆AICc
0.00
2.72
3.91
4.11
4.48
4.85
4.88
5.25
5.92
9.08
Posthoc models
Life zone, Mass
Life zone, Young per year
Life zone, Litters per year
Life zone, Litter size
Life zone, Longevity
Life zone, Daily rhythm
Life zone, Annual rhythm
Lize zone, Diet
3
3
3
3
3
4
4
5
37.50
37.72
37.87
38.00
38.45
39.37
40.18
41.80
1.57
1.79
1.94
2.07
2.52
3.44
4.25
5.87
Upper Limit Range Change Models
Life zone
Longevity
Mass
Daily rhythm
Litters per year
Constant (.)
Young per year
Annual rhythm
Litter size
Diet
K
2
2
2
3
2
1
2
3
2
4
AICc
17.94
21.19
23.86
24.74
24.81
25.11
25.75
26.56
27.45
29.91
∆AICc
0.00
3.25
5.92
6.80
6.87
7.17
7.81
8.62
9.51
11.97
Posthoc models
Life zone, Longevity
Life zone, Litters per year
3
3
14.41
16.56
-3.53
-1.38
50
AIC Wt (w)
0.51
0.13
0.07
0.07
0.05
0.05
0.04
0.04
0.03
0.01
AIC Wt (w)
0.72
0.14
0.04
0.02
0.02
0.02
0.01
0.01
0.01
0.00
Supporting Online Material
Life zone, Mass
Life zone, Young per year
Life zone, Litter size
Life zone, Daily rhythm
Life zone, Annual rhythm
Life zone, Diet
Moritz et al.
3
3
3
4
4
5
51
17.21
18.51
20.41
21.88
22.10
24.19
-0.73
0.57
2.47
3.94
4.16
6.25
Supporting Online Material
Moritz et al.
Table S6. Small mammal life history dataset used for tests of elevational range shift in Table S5.
Species
Chaetodipus californicus
Dipodomys heermanni
Marmota flaviventris
Microtus californicus
Microtus longicaudus
Microtus montanus
Neotoma cinerea
Neotoma macrotis
Ochotona princeps
Peromyscus boylii
Peromyscus maniculatus
Peromyscus truei
Reithrodontomys megaloti
Sorex monticolus
Sorex ornatus
Sorex palustris
Sorex trowbridgii
Spermophilus beecheyi
Spermophilus beldingi
Spermophilus lateralis
Tamias alpinus
Tamias quadrimaculatus
Tamias senex
Tamias speciosus
Tamiasciurus douglasi
Thomomys bottae
Thomomys monticola
Zapus princeps
Mass (g)
25
70
4500
60
65
45
450
350
130
24
18
30
10
4
4
15
6
700
300
250
35
80
80
50
250
120
90
30
Longevity (yrs)
1
3
5
0.5
0.5
0.5
3
3
3
1
0.5
0.5
0.5
0.5
0.5
0.5
0.5
3
3
3
2
2
2
2
4
2
2
2
Litter_size
4
3
5
6
4
6
4
3
4
3
4
4
4
6
5
6
4
6
6
4
4
4
4
4
5
6
4
4
52
Daily_rhythm
nocturnal
nocturnal
diurnal
both
both
both
nocturnal
nocturnal
diurnal
nocturnal
nocturnal
nocturnal
nocturnal
both
both
both
both
diurnal
diurnal
diurnal
diurnal
diurnal
diurnal
diurnal
diurnal
both
both
nocturnal
Annual_rhythm
non-hibernator
non-hibernator
obligate hibernator
non-hibernator
non-hibernator
non-hibernator
non-hibernator
non-hibernator
non-hibernator
non-hibernator
non-hibernator
non-hibernator
non-hibernator
non-hibernator
non-hibernator
non-hibernator
non-hibernator
obligate hibernator
obligate hibernator
obligate hibernator
facultative hibernator
facultative hibernator
facultative hibernator
facultative hibernator
non-hibernator
non-hibernator
non-hibernator
obligate hibernator
Food
granivore
granivore
herbivore
herbivore
herbivore
herbivore
herbivore
herbivore
herbivore
granivore
omnivore
omnivore
omnivore
insectivore
insectivore
insectivore
insectivore
omnivore
herbivore
omnivore
granivore
granivore
granivore
granivore
granivore
herbivore
herbivore
omnivore
Litters/yr
Young/yr
2
2
1
4
3
4
2
1
2
2
3
2
2
2
2
2
2
1
1
1
1
1
1
1
2
2
1
1
6
5
5
24
12
24
8
3
6
6
12
8
8
9
8
12
8
6
6
4
4
4
4
4
8
12
4
4
Supporting Online Material
Moritz et al.
Supplementary Literature Cited
S1.
S2.
S3.
S4.
S5.
S6.
S7.
S8.
S9.
S10.
S11.
S. LaDochy, R. Medina, W. Patzert, Climate Research 33, 159 (2007).
C. I. Millar, R. D. Westfall, D. L. Delany, J. C. King, L. J. Graumlich, Arctic Antarctic
and Alpine Research 36, 181 (2004).
J. Parra, W. Monahan, Global Change Biology 14, 2115 (2008).
J. Grinnell, T. Storer, Animal Life in the Yosemite. (University California Press,
Berkeley, California, 1924), pp. 752
K. P. Burnham, D. R. Anderson, Model selection and inference: a practical theoretic
approach. (Springer-Verlag., New York, 2002).
D. I. MacKenzie et al., Inferring patterns and dynamics of species occurrence. (Elsevier,
San Diego, 2006).
G. C. White, K. P. Burnham, Bird Study 46, 120 (1999).
R. K. Colwell, C. X. Mao, J. Chang, Ecology 85, 2717 (2004).
A. Chao, in Encyclopedia of Statistical Sciences, N. Balakrishnan, C. B. Read, B.
Vidakovic, Eds. (Wiley, New York, 2005).
A. Chao, R. L. Chazdon, R. K. Colwell, T.-J. Shen, Ecology Letters 8, 148 (2005).
R. J. Wilson, D. Gutierrez, J. Gutierrez, V. J. Monserrat, Global Change Biology 13,
1873 (2007).
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